> For the complete documentation index, see [llms.txt](https://docs.lleverage.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.lleverage.ai/run-operations/agent/agent-context/memory.md). # Memory Understand how Memory carries useful context across Agent sessions. Memory helps the Agent carry useful context across sessions instead of treating every conversation as completely new. It is persistent working context. It is **not** a replacement for the ERP, a maintained policy, a governed mapping or another authoritative source. ## Memory can be created and retrieved automatically Supported Agent work can contribute persistent context after a session, including extracted facts and reusable reflections from the conversation. Relevant Memory can also be retrieved automatically for later Agent runs when it matches the work being done. You do not need to paste the entire history into every new session or explicitly ask the Agent to remember every useful detail. This process is selective. Memory is not a complete transcript, and something being said once does not make it a guaranteed durable rule. ## The three Memory layers Memory separates persistent context into: * **Observations** — raw or recent context, such as past sessions, reflections and ingested material; * **Memories** — distilled reusable facts, preferences and rules of thumb; * **Knowledge** — more deliberately curated reference context. These layers describe how context was formed. They are not a universal ranking of truth. A current system value can outrank a remembered value. An approved policy can outrank an observation. A customer-specific rule can outrank generic industry guidance. ## Memory and Skills are different **Memory** helps the Agent remember context. **Skills** define a reusable way of doing a job. When a Skill is active, its reviewed method should guide the recurring task. Memory can add useful context, but it should not silently override the Skill or another maintained source. If a remembered rule repeatedly conflicts with the maintained method, correct the owning layer. ## What you see in a session The session's **Memory** area gives visibility into persistent context around the current work. Use it as supporting evidence. It is not intended to be a perfect trace of every retrieval decision or proof that everything shown determined the final answer. ## Memory and Channels Slack or Teams do not turn Memory into one unrestricted organisation-wide pool. The run still follows the acting user's authorised scope and the conversation context. When work should clearly stay inside one Project, pin the conversation to that Project. Builders can inspect and correct broader Project Memory under **Intelligence → Memory**. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.lleverage.ai/run-operations/agent/agent-context/memory.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.